Transformation of Conjuntival intraepithelial neoplasia into Squamous Cell Carcinoma despite topical treatment with Interferon α2b

Presentamos el caso de una mujer de 69 años de edad que acude por aparición de una tumoración en ojo derecho (OD) de 3 meses de evolución. En la exploración se observó una lesión en conjuntiva nasal de 3x8mm. El estudio de citología por impresión de la lesión, mostró una neoplasia intraepitelial conjuntival (CIN). Se inició tratamiento con interferón α2B tópico (IFN-α2b) 1 MUI/ml. A pesar de una disminución inicial de su tamaño (2x5mm), posteriormente se observó un nuevo crecimiento, por lo que se decidió tratamiento quirúrgico. El estudio histopatológico de la lesión confirmó el diagnóstico de carcinoma de células escamosas (CCE) moderadamente diferenciado con márgenes afectos. El tratamiento de la CIN con IFN-α2b ha impuesto como tratamiento de elección frente a la resección quirúrgica, dados los buenos resultados obtenidos, escasa recurrencia y pocos.Clinical case: A 69 year old woman presented with a conjunctival mass in her right eye (OD) for the previous 3 months. It was observed a mass of 3x8mm involving the nasal conjunctiva. Citolology study was performed showing a conjunctival intraepithelial neoplasia (NIC). Initially the lesion decreased in size (2x5mm) after topical interferon α2b (IFN-α2b) 1 MUI/ml treatment was prescribed. However, 6 months later, a new growth of the NIC was observed, so we decided surgical treatment. Histopathological study confirmed the diagnosis of conjunctival squamous cell carcinoma (SCC). Conclusions : Treatment with IFN-α2b is being preferred to surgical excision for NIC, due to its good results obtained, low recurrence and its few adverse effects. However, ineffective cases and progression to SCC of conjunctiva have been reported

The effects of numeracy and presentation format on judgments of contingency

Covariation information can be used to infer whether a causal link plausibly exists between two dichotomous variables, and such judgments of contingency are central to many critical and everyday decisions. However, individuals do not always interpret and integrate covariation information effectively, an issue that may be compounded by limited numeracy skills, and they often resort to the use of heuristics, which can result in inaccurate judgments. This experiment investigated whether presenting covariation information in a composite bar chart increased accuracy of contingency judgments, and whether it can mitigate errors driven by low numeracy skills. Participants completed an online questionnaire, which consisted of an 11-item numeracy scale and three covariation problems that varied in level of difficulty, involving a fictitious fertilizer and its impact on whether a plant bloomed or not. Half received summary covariation information in a composite bar chart, and half in a 2 × 2 matrix that summarized event frequencies. Viewing the composite bar charts increased accuracy of individuals both high and low in numeracy, regardless of problem difficulty, resulted in more consistent judgments that were closer to the normatively correct value, and increased the likelihood of detecting the correct direction of association. Findings are consistent with prior work, suggesting that composite bar charts are an effective way to improve covariation judgment and have potential for use in the domain of health risk communication

Making effective use of healthcare data using data-to-text technology

Healthcare organizations are in a continuous effort to improve health outcomes, reduce costs and enhance patient experience of care. Data is essential to measure and help achieving these improvements in healthcare delivery. Consequently, a data influx from various clinical, financial and operational sources is now overtaking healthcare organizations and their patients. The effective use of this data, however, is a major challenge. Clearly, text is an important medium to make data accessible. Financial reports are produced to assess healthcare organizations on some key performance indicators to steer their healthcare delivery. Similarly, at a clinical level, data on patient status is conveyed by means of textual descriptions to facilitate patient review, shift handover and care transitions. Likewise, patients are informed about data on their health status and treatments via text, in the form of reports or via ehealth platforms by their doctors. Unfortunately, such text is the outcome of a highly labour-intensive process if it is done by healthcare professionals. It is also prone to incompleteness, subjectivity and hard to scale up to different domains, wider audiences and varying communication purposes. Data-to-text is a recent breakthrough technology in artificial intelligence which automatically generates natural language in the form of text or speech from data. This chapter provides a survey of data-to-text technology, with a focus on how it can be deployed in a healthcare setting. It will (1) give an up-to-date synthesis of data-to-text approaches, (2) give a categorized overview of use cases in healthcare, (3) seek to make a strong case for evaluating and implementing data-to-text in a healthcare setting, and (4) highlight recent research challenges.Comment: 27 pages, 2 figures, book chapte

We are safe but you are not: exploring comparative optimism and cyber bullying

Individuals tend to believe that when comparing themselves to others they are less vulnerable to potential risks. This is referred to as comparative optimism, whereby individuals believe that they are immune from negative experiences that can happen to others. The current study examined comparative optimism judgements for the likelihood of experiencing cyber bullying. Comparative optimism was examined in three age groups: older adolescents (n = 130, 57% female, Mage = 16.82, SDage = .38), emerging adults (n = 355, 92% female, Mage = 19.26, SDage = .27), and adults (n = 147, 66% female, Mage = 33.24, SDage = 9.77). All participants reported the likelihood that they, their friends, other students [forum users] younger than them, other students [forum users] their age, people older than them, and strangers would experience cyber bullying. Participants displayed an optimistic bias, reporting that they were less likely to experience cyber bullying than others. However, the relative risk of experiencing cyber bullying varied according to comparator group. Comparator groups that were socially close to the participants (e.g. friends) were generally rated as less likely to experience cyber bullying than socially distant comparator groups (e.g. strangers). Also, comparator groups that were younger than the participants were consistently judged to be most at risk of experiencing cyber bullying. Together, the findings have implications for the design of anti-cyber bullying interventions and campaigns to promote digital safety